Using AI to Improve Change Management for AI Adoption

Leaders struggling with underperforming AI projects often report that initial successes tail off and expected ROI is not achieved. [1] In many cases, these leaders are not handling change management effectively. [1] They use outdated methods and techniques, treating change management as a commodity or a box-checking exercise instead of a strategic advantage. [1] This approach is insufficient for AI, which is transformative by definition and makes change a constant part of an organization's operations. [1]

Because AI brings constant change, organizations cannot rely on standardized stakeholder interviews, communication plans, and training regimens used in past software rollouts. [1] However, AI itself can be used to reinvent change management for the AI era. [1] By using AI, organizations can make the change management process more continuous, employee-centered, and measurable. [1] This transforms change management from a one-time project into an ongoing organizational capability. [1]

The failure to see expected ROI from AI projects often points to a misalignment between the transformative nature of AI and the rigid, outdated methods used to implement it. Organizations are treating AI like a standard software rollout, ignoring that AI requires ongoing adaptation. By leveraging AI to continuously manage change, companies can create a more responsive and employee-centric adoption strategy. What the sources don't address: Specific examples of how AI tools are actively being deployed to measure or manage these continuous, employee-centered change processes.